Statsig Developer Tier
StatsigReviews from AWS customer
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Integration and first experiment
What do you like best about the product?
Fast support, easy integration via libraries
What do you dislike about the product?
It takes a while to understand how configuration of whole thing like key, environment and experiment works
What problems is the product solving and how is that benefiting you?
It solves decisions if new features are valuable for customers
Effective and Powerful Experimentation Tool with a Learning Curve
What do you like best about the product?
What I like most about Statsig is how easy it is to set up experiments and actually understand the results. The built-in metrics and holdouts save a lot of time, and I like that it shows lift and significance clearly without needing to dig through a bunch of stats. It’s been really helpful for making quick, data-informed decisions.
What do you dislike about the product?
There are many powerful features our team could potentially leverage, but it’s been challenging to fully understand how to use them correctly. Needs more onboarding sessions!
What problems is the product solving and how is that benefiting you?
Statsig helps solve the challenge of running reliable experiments and rolling out features safely. It makes it easier to test ideas quickly with real users and measure impact without guesswork. For me, that means faster decision-making based on data, less risk when launching new features, and a clearer understanding of what’s actually working.
Huge Upgrade!
What do you like best about the product?
Statsig has been awesome to work with. The integration was super smooth — getting it into our codebase took barely any time, and the SDKs were super easy to understand. Everything just worked, which was a nice change of pace from our in-house A/B testing solution
The UI is also a huge plus. It's clean, intuitive, and makes it easy to manage feature flags and experiments without having to dig through a bunch of settings. I especially love the dashboards — they give a clear view of how things are performing, and the segmentation features are great for diving into how different groups are behaving. It's powerful, but still easy to use, which is rare.
The UI is also a huge plus. It's clean, intuitive, and makes it easy to manage feature flags and experiments without having to dig through a bunch of settings. I especially love the dashboards — they give a clear view of how things are performing, and the segmentation features are great for diving into how different groups are behaving. It's powerful, but still easy to use, which is rare.
What do you dislike about the product?
Not much, honestly. If I had to pick something, maybe some of the deeper features could use a bit more guidance the first time around. But once you get the hang of it, it all makes sense. The docs are solid, and their support is super helpful.
What problems is the product solving and how is that benefiting you?
Statsig makes it really easy to roll out features safely and run experiments without a ton of overhead. Before, we were either hardcoding flags or using super manual setups to A/B test things — which was time-consuming and not super reliable.
Best feature flag platform for startups
What do you like best about the product?
The ability to change the value of feature flag based on parameters across any environments
What do you dislike about the product?
There is not automated rollback of feature flag if some metric is bad.
What problems is the product solving and how is that benefiting you?
Able to turn on and turn off the feature flag outside of the standard release cycle.
Relatively easy to use
What do you like best about the product?
The UI is very easy to use to set up gates, experiments, configs. High level documentation is easy to follow and understand, and I found some YouTube videos that further explain concepts which is great. Slack support from the Statsig team was appreciated!
What do you dislike about the product?
Setting up the SDK had some limited documentation and we ran into a unique bug about login and value flashing that we didn't really have any reference for. Additionally there's some limitations about experiment setup and environments - you can choose different distributions for different environments but you can't choose different populations (50% of population in prod vs 100% of population in staging).
What problems is the product solving and how is that benefiting you?
We primarily use Statsig for A/B testing as well as feature rollout. The experiment support in Statsig is quite good with the ability to track primary and secondary metrics, set up holdout groups easily, and view comprehensive results after enough time has passed.
Lacking the
What do you like best about the product?
Statsig is very robust and have been very useful in setting up the experiments.
We have integrated Statsig with our vendors like SFMC. CDP and it has supported pretty well.
We have integrated Statsig with our vendors like SFMC. CDP and it has supported pretty well.
What do you dislike about the product?
We are doing POC with our vendor and since, we would like to know adhoc investigation and do lot of monitoring. We would need dashboards. We tried running dashboards in stastig but we felt it lacks maturity and can show only basic graphs. In future, this could be good opportunity to make complex dashboards as leadership have access to stastig and sometimes don't have tableau/databricks notebook access.
What problems is the product solving and how is that benefiting you?
Statsig have been helping our team in setting up and analyzing experiments and we have also use feature flag of statsig.
Earlier we were using RCS for feature flag but we found that was creating lot of bugs. Moving to feature flag have been one of the success stories for using stastig.
Earlier we were using RCS for feature flag but we found that was creating lot of bugs. Moving to feature flag have been one of the success stories for using stastig.
Easy to self-serve creating experiment dashboards and deep-dive results analysis by cohorts
What do you like best about the product?
I appreciate that I can self-serve create experiment dashboards and not having to wait on data science resources to create them to quickly monitor the health immediately after experiment launch. The ease of use of being able to deep-dive analysis by different cohorts defined by the data science team is very helpful as well.
What do you dislike about the product?
This is more of a setup rather than a downfall, but though I enjoy the self-serve aspect, it required a lot of coordination and time to get there. In order to onboard new funnel events to measure as primary and secondary metrics or even new cohorts, it requires data science resources. I also wish I can rerun past queries without having to clone it, or even save past queries but adjust the experiment id.
What problems is the product solving and how is that benefiting you?
Self-serve experiment dashboards and experiment analysis. It's helping me get to a decision quicker and run additional experiments faster.
Statsig always provides timely and high quality support
What do you like best about the product?
The Statsig team is highly skilled and any person on support is able to support most of the products and features they provide. During both the support and the first time we integrated with the platform Statsig provided easy to use documentation including code examples which accelerated our rate of integration. They provide a high number of features and additionally they implemented new features we requested. Each of the new features was delivered in high quality. The tooling works as expected and each of their design decisions is well thought through. The platform has no problem handling high traffic.
What do you dislike about the product?
The rate at which they add new features is very high and sometimes a new feature is enabled before we had a chance to onboard our internal stakeholders.
What problems is the product solving and how is that benefiting you?
It's a complete platform for experimentation. They provide user randomisation, event collection and result analysis which enables informed decision making.
Best way to rollout your features
What do you like best about the product?
1. Easy to setup
2. Different ways to setup - config and gates
3. Multiple ways to configure - by company, segment, user, os......
4. Active and continuous supportive community
5. 99.99% uptime
2. Different ways to setup - config and gates
3. Multiple ways to configure - by company, segment, user, os......
4. Active and continuous supportive community
5. 99.99% uptime
What do you dislike about the product?
Once, I'd set up some Datadog<>Statsig integration flags which gets auto disable and enable the flag based on the linked DD monitor but I found that once it'd a fault where this integration was not working properly and it costed us but yeah the team support is great, they fixed the issue within 2 hours. So, the only downside is they should actively review their third party integrations and their workings.
What problems is the product solving and how is that benefiting you?
It's helping in rolling out the new changes smoothly and behind the Statsig's safe protection.
Statsig is fast, flexible, and a great platform for data-driven teams.
What do you like best about the product?
Statsig makes it easy to run experiments and manage feature flags at scale. It’s fast, intuitive, and integrates seamlessly with our workflow. Turning on experiments, gating features, and rolling out changes is smooth and reliable. The real-time analytics are especially powerful, letting us quickly see feature performance across metrics and make confident, data-driven decisions without manual analysis.
What do you dislike about the product?
Statsig is really an awesome platform but there are a few areas which could be better. UI sometimes feels a bit cluttered especially when there are too many experiments or feature gates to manage. It could have a better-filtering grouping on the experiment results view. More advanced filtering and grouping on the experiment results view.
What problems is the product solving and how is that benefiting you?
Statsig enables us to very easily and precisely perform A/B tests hence solving the problem of making product decisions without clear data. By connecting experiments to real-time metrics, we can quickly figure out what’s going on and what’s not. It’s improved our ability to release features with confidence, reduce guesswork, and make smarter, faster product decisions.
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